[ https://issues.apache.org/jira/browse/CARBONDATA-1783?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Chetan Bhat updated CARBONDATA-1783: ------------------------------------ Description: Steps :- Spark submit thrift server is started using the command - bin/spark-submit --master yarn-client --executor-memory 10G --executor-cores 5 --driver-memory 5G --num-executors 3 --class org.apache.carbondata.spark.thriftserver.CarbonThriftServer /srv/spark2.2Bigdata/install/spark/sparkJdbc/carbonlib/carbondata_2.11-1.3.0-SNAPSHOT-shade-hadoop2.7.2.jar "hdfs://hacluster/user/hive/warehouse/carbon.store" Spark shell is launched using the command - bin/spark-shell --master yarn-client --executor-memory 10G --executor-cores 5 --driver-memory 5G --num-executors 3 --jars /srv/spark2.2Bigdata/install/spark/sparkJdbc/carbonlib/carbondata_2.11-1.3.0-SNAPSHOT-shade-hadoop2.7.2.jar From Spark shell user creates table and loads data in the table as shown below. import java.io.{File, PrintWriter} import java.net.ServerSocket import org.apache.spark.sql.{CarbonEnv, SparkSession} import org.apache.spark.sql.hive.CarbonRelation import org.apache.spark.sql.streaming.{ProcessingTime, StreamingQuery} import org.apache.carbondata.core.constants.CarbonCommonConstants import org.apache.carbondata.core.util.CarbonProperties import org.apache.carbondata.core.util.path.{CarbonStorePath, CarbonTablePath} CarbonProperties.getInstance().addProperty(CarbonCommonConstants.CARBON_TIMESTAMP_FORMAT, "yyyy/MM/dd") import org.apache.spark.sql.CarbonSession._ val carbonSession = SparkSession. builder(). appName("StreamExample"). getOrCreateCarbonSession("hdfs://hacluster/user/hive/warehouse/carbon.store") carbonSession.sparkContext.setLogLevel("INFO") def sql(sql: String) = carbonSession.sql(sql) def writeSocket(serverSocket: ServerSocket): Thread = { val thread = new Thread() { override def run(): Unit = { // wait for client to connection request and accept val clientSocket = serverSocket.accept() val socketWriter = new PrintWriter(clientSocket.getOutputStream()) var index = 0 for (_ <- 1 to 1000) { // write 5 records per iteration for (_ <- 0 to 100) { index = index + 1 socketWriter.println(index.toString + ",name_" + index + ",city_" + index + "," + (index * 10000.00).toString + ",school_" + index + ":school_" + index + index + "$" + index) } socketWriter.flush() Thread.sleep(2000) } socketWriter.close() System.out.println("Socket closed") } } thread.start() thread } def startStreaming(spark: SparkSession, tablePath: CarbonTablePath, tableName: String, port: Int): Thread = { val thread = new Thread() { override def run(): Unit = { var qry: StreamingQuery = null try { val readSocketDF = spark.readStream .format("socket") .option("host", "10.18.98.34") .option("port", port) .load() qry = readSocketDF.writeStream .format("carbondata") .trigger(ProcessingTime("5 seconds")) .option("checkpointLocation", tablePath.getStreamingCheckpointDir) .option("tablePath", tablePath.getPath).option("tableName", tableName) .start() qry.awaitTermination() } catch { case ex: Throwable => ex.printStackTrace() println("Done reading and writing streaming data") } finally { qry.stop() } } } thread.start() thread } val streamTableName = "all_datatypes_2048" sql(s"create table all_datatypes_2048 (imei string,deviceInformationId int,MAC string,deviceColor string,device_backColor string,modelId string,marketName string,AMSize string,ROMSize string,CUPAudit string,CPIClocked string,series string,productionDate timestamp,bomCode string,internalModels string, deliveryTime string, channelsId string, channelsName string , deliveryAreaId string, deliveryCountry string, deliveryProvince string, deliveryCity string,deliveryDistrict string, deliveryStreet string, oxSingleNumber string, ActiveCheckTime string, ActiveAreaId string, ActiveCountry string, ActiveProvince string, Activecity string, ActiveDistrict string, ActiveStreet string, ActiveOperatorId string, Active_releaseId string, Active_EMUIVersion string, Active_operaSysVersion string, Active_BacVerNumber string, Active_BacFlashVer string, Active_webUIVersion string, Active_webUITypeCarrVer string,Active_webTypeDataVerNumber string, Active_operatorsVersion string, Active_phonePADPartitionedVersions string, Latest_YEAR int, Latest_MONTH int, Latest_DAY Decimal(30,10), Latest_HOUR string, Latest_areaId string, Latest_country string, Latest_province string, Latest_city string, Latest_district string, Latest_street string, Latest_releaseId string, Latest_EMUIVersion string, Latest_operaSysVersion string, Latest_BacVerNumber string, Latest_BacFlashVer string, Latest_webUIVersion string, Latest_webUITypeCarrVer string, Latest_webTypeDataVerNumber string, Latest_operatorsVersion string, Latest_phonePADPartitionedVersions string, Latest_operatorId string, gamePointDescription string,gamePointId double,contractNumber BigInt) STORED BY 'org.apache.carbondata.format' TBLPROPERTIES('streaming'='true','table_blocksize'='2048')") sql(s"LOAD DATA INPATH 'hdfs://hacluster/chetan/100_olap_C20.csv' INTO table all_datatypes_2048 options ('DELIMITER'=',', 'BAD_RECORDS_ACTION'='FORCE','FILEHEADER'='imei,deviceInformationId,MAC,deviceColor,device_backColor,modelId,marketName,AMSize,ROMSize,CUPAudit,CPIClocked,series,productionDate,bomCode,internalModels,deliveryTime,channelsId,channelsName,deliveryAreaId,deliveryCountry,deliveryProvince,deliveryCity,deliveryDistrict,deliveryStreet,oxSingleNumber,contractNumber,ActiveCheckTime,ActiveAreaId,ActiveCountry,ActiveProvince,Activecity,ActiveDistrict,ActiveStreet,ActiveOperatorId,Active_releaseId,Active_EMUIVersion,Active_operaSysVersion,Active_BacVerNumber,Active_BacFlashVer,Active_webUIVersion,Active_webUITypeCarrVer,Active_webTypeDataVerNumber,Active_operatorsVersion,Active_phonePADPartitionedVersions,Latest_YEAR,Latest_MONTH,Latest_DAY,Latest_HOUR,Latest_areaId,Latest_country,Latest_province,Latest_city,Latest_district,Latest_street,Latest_releaseId,Latest_EMUIVersion,Latest_operaSysVersion,Latest_BacVerNumber,Latest_BacFlashVer,Latest_webUIVersion,Latest_webUITypeCarrVer,Latest_webTypeDataVerNumber,Latest_operatorsVersion,Latest_phonePADPartitionedVersions,Latest_operatorId,gamePointId,gamePointDescription')") val carbonTable = CarbonEnv.getInstance(carbonSession).carbonMetastore. lookupRelation(Some("default"), streamTableName)(carbonSession).asInstanceOf[CarbonRelation].carbonTable val tablePath = CarbonStorePath.getCarbonTablePath(carbonTable.getAbsoluteTableIdentifier) val port = 8007 val serverSocket = new ServerSocket(port) val socketThread = writeSocket(serverSocket) val streamingThread = startStreaming(carbonSession, tablePath, streamTableName, port) While the streaming load is in progress from Beeline user executes the below select filter query select imei,gamePointId, channelsId,series from all_datatypes_2048 where channelsId >=10 OR channelsId <=1 and series='7Series'; *Issue : The select filter query fails with exception as shown below.* 0: jdbc:hive2://10.18.98.34:23040> select imei,gamePointId, channelsId,series from all_datatypes_2048 where channelsId >=10 OR channelsId <=1 and series='7Series'; Error: org.apache.spark.SparkException: Job aborted due to stage failure: Task 6 in stage 773.0 failed 4 times, most recent failure: Lost task 6.3 in stage 773.0 (TID 33727, BLR1000014269, executor 14): java.io.IOException: Failed to filter row in vector reader at org.apache.carbondata.hadoop.streaming.CarbonStreamRecordReader.scanBlockletAndFillVector(CarbonStreamRecordReader.java:423) at org.apache.carbondata.hadoop.streaming.CarbonStreamRecordReader.nextColumnarBatch(CarbonStreamRecordReader.java:317) at org.apache.carbondata.hadoop.streaming.CarbonStreamRecordReader.nextKeyValue(CarbonStreamRecordReader.java:298) at org.apache.carbondata.spark.rdd.CarbonScanRDD$$anon$1.hasNext(CarbonScanRDD.scala:298) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.scan_nextBatch$(Unknown Source) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377) at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:231) at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:225) at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:826) at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:826) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) at org.apache.spark.scheduler.Task.run(Task.scala:99) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) at java.lang.Thread.run(Thread.java:745) Caused by: org.apache.carbondata.core.scan.expression.exception.FilterUnsupportedException: [B cannot be cast to org.apache.spark.unsafe.types.UTF8String at org.apache.spark.sql.SparkUnknownExpression.evaluate(SparkUnknownExpression.scala:50) at org.apache.carbondata.core.scan.expression.conditional.GreaterThanEqualToExpression.evaluate(GreaterThanEqualToExpression.java:38) at org.apache.carbondata.core.scan.filter.executer.RowLevelFilterExecuterImpl.applyFilter(RowLevelFilterExecuterImpl.java:272) at org.apache.carbondata.core.scan.filter.executer.OrFilterExecuterImpl.applyFilter(OrFilterExecuterImpl.java:49) at org.apache.carbondata.hadoop.streaming.CarbonStreamRecordReader.scanBlockletAndFillVector(CarbonStreamRecordReader.java:418) ... 20 more Driver stacktrace: (state=,code=0) Expected : The select filter query should be success without error/exception. was: Steps :- Spark submit thrift server is started using the command - bin/spark-submit --master yarn-client --executor-memory 10G --executor-cores 5 --driver-memory 5G --num-executors 3 --class org.apache.carbondata.spark.thriftserver.CarbonThriftServer /srv/spark2.2Bigdata/install/spark/sparkJdbc/carbonlib/carbondata_2.11-1.3.0-SNAPSHOT-shade-hadoop2.7.2.jar "hdfs://hacluster/user/hive/warehouse/carbon.store" Spark shell is launched using the command - bin/spark-shell --master yarn-client --executor-memory 10G --executor-cores 5 --driver-memory 5G --num-executors 3 --jars /srv/spark2.2Bigdata/install/spark/sparkJdbc/carbonlib/carbondata_2.11-1.3.0-SNAPSHOT-shade-hadoop2.7.2.jar From Spark shell user creates table and loads data in the table as shown below. import java.io.{File, PrintWriter} import java.net.ServerSocket import org.apache.spark.sql.{CarbonEnv, SparkSession} import org.apache.spark.sql.hive.CarbonRelation import org.apache.spark.sql.streaming.{ProcessingTime, StreamingQuery} import org.apache.carbondata.core.constants.CarbonCommonConstants import org.apache.carbondata.core.util.CarbonProperties import org.apache.carbondata.core.util.path.{CarbonStorePath, CarbonTablePath} CarbonProperties.getInstance().addProperty(CarbonCommonConstants.CARBON_TIMESTAMP_FORMAT, "yyyy/MM/dd") import org.apache.spark.sql.CarbonSession._ val carbonSession = SparkSession. builder(). appName("StreamExample"). getOrCreateCarbonSession("hdfs://hacluster/user/hive/warehouse/carbon.store") carbonSession.sparkContext.setLogLevel("INFO") def sql(sql: String) = carbonSession.sql(sql) def writeSocket(serverSocket: ServerSocket): Thread = { val thread = new Thread() { override def run(): Unit = { // wait for client to connection request and accept val clientSocket = serverSocket.accept() val socketWriter = new PrintWriter(clientSocket.getOutputStream()) var index = 0 for (_ <- 1 to 1000) { // write 5 records per iteration for (_ <- 0 to 100) { index = index + 1 socketWriter.println(index.toString + ",name_" + index + ",city_" + index + "," + (index * 10000.00).toString + ",school_" + index + ":school_" + index + index + "$" + index) } socketWriter.flush() Thread.sleep(2000) } socketWriter.close() System.out.println("Socket closed") } } thread.start() thread } def startStreaming(spark: SparkSession, tablePath: CarbonTablePath, tableName: String, port: Int): Thread = { val thread = new Thread() { override def run(): Unit = { var qry: StreamingQuery = null try { val readSocketDF = spark.readStream .format("socket") .option("host", "10.18.98.34") .option("port", port) .load() qry = readSocketDF.writeStream .format("carbondata") .trigger(ProcessingTime("5 seconds")) .option("checkpointLocation", tablePath.getStreamingCheckpointDir) .option("tablePath", tablePath.getPath).option("tableName", tableName) .start() qry.awaitTermination() } catch { case ex: Throwable => ex.printStackTrace() println("Done reading and writing streaming data") } finally { qry.stop() } } } thread.start() thread } val streamTableName = "all_datatypes_2048" sql(s"create table all_datatypes_2048 (imei string,deviceInformationId int,MAC string,deviceColor string,device_backColor string,modelId string,marketName string,AMSize string,ROMSize string,CUPAudit string,CPIClocked string,series string,productionDate timestamp,bomCode string,internalModels string, deliveryTime string, channelsId string, channelsName string , deliveryAreaId string, deliveryCountry string, deliveryProvince string, deliveryCity string,deliveryDistrict string, deliveryStreet string, oxSingleNumber string, ActiveCheckTime string, ActiveAreaId string, ActiveCountry string, ActiveProvince string, Activecity string, ActiveDistrict string, ActiveStreet string, ActiveOperatorId string, Active_releaseId string, Active_EMUIVersion string, Active_operaSysVersion string, Active_BacVerNumber string, Active_BacFlashVer string, Active_webUIVersion string, Active_webUITypeCarrVer string,Active_webTypeDataVerNumber string, Active_operatorsVersion string, Active_phonePADPartitionedVersions string, Latest_YEAR int, Latest_MONTH int, Latest_DAY Decimal(30,10), Latest_HOUR string, Latest_areaId string, Latest_country string, Latest_province string, Latest_city string, Latest_district string, Latest_street string, Latest_releaseId string, Latest_EMUIVersion string, Latest_operaSysVersion string, Latest_BacVerNumber string, Latest_BacFlashVer string, Latest_webUIVersion string, Latest_webUITypeCarrVer string, Latest_webTypeDataVerNumber string, Latest_operatorsVersion string, Latest_phonePADPartitionedVersions string, Latest_operatorId string, gamePointDescription string,gamePointId double,contractNumber BigInt) STORED BY 'org.apache.carbondata.format' TBLPROPERTIES('streaming'='true','table_blocksize'='2048')") sql(s"LOAD DATA INPATH 'hdfs://hacluster/chetan/100_olap_C20.csv' INTO table all_datatypes_2048 options ('DELIMITER'=',', 'BAD_RECORDS_ACTION'='FORCE','FILEHEADER'='imei,deviceInformationId,MAC,deviceColor,device_backColor,modelId,marketName,AMSize,ROMSize,CUPAudit,CPIClocked,series,productionDate,bomCode,internalModels,deliveryTime,channelsId,channelsName,deliveryAreaId,deliveryCountry,deliveryProvince,deliveryCity,deliveryDistrict,deliveryStreet,oxSingleNumber,contractNumber,ActiveCheckTime,ActiveAreaId,ActiveCountry,ActiveProvince,Activecity,ActiveDistrict,ActiveStreet,ActiveOperatorId,Active_releaseId,Active_EMUIVersion,Active_operaSysVersion,Active_BacVerNumber,Active_BacFlashVer,Active_webUIVersion,Active_webUITypeCarrVer,Active_webTypeDataVerNumber,Active_operatorsVersion,Active_phonePADPartitionedVersions,Latest_YEAR,Latest_MONTH,Latest_DAY,Latest_HOUR,Latest_areaId,Latest_country,Latest_province,Latest_city,Latest_district,Latest_street,Latest_releaseId,Latest_EMUIVersion,Latest_operaSysVersion,Latest_BacVerNumber,Latest_BacFlashVer,Latest_webUIVersion,Latest_webUITypeCarrVer,Latest_webTypeDataVerNumber,Latest_operatorsVersion,Latest_phonePADPartitionedVersions,Latest_operatorId,gamePointId,gamePointDescription')") val carbonTable = CarbonEnv.getInstance(carbonSession).carbonMetastore. lookupRelation(Some("default"), streamTableName)(carbonSession).asInstanceOf[CarbonRelation].carbonTable val tablePath = CarbonStorePath.getCarbonTablePath(carbonTable.getAbsoluteTableIdentifier) val port = 8007 val serverSocket = new ServerSocket(port) val socketThread = writeSocket(serverSocket) val streamingThread = startStreaming(carbonSession, tablePath, streamTableName, port) While the streaming load is in progress from Beeline user executes the below select filter query select imei,gamePointId, channelsId,series from all_datatypes_2048 where channelsId >=10 OR channelsId <=1 and series='7Series'; Issue : The select filter query fails with exception as shown below. 0: jdbc:hive2://10.18.98.34:23040> select imei,gamePointId, channelsId,series from all_datatypes_2048 where channelsId >=10 OR channelsId <=1 and series='7Series'; Error: org.apache.spark.SparkException: Job aborted due to stage failure: Task 6 in stage 773.0 failed 4 times, most recent failure: Lost task 6.3 in stage 773.0 (TID 33727, BLR1000014269, executor 14): java.io.IOException: Failed to filter row in vector reader at org.apache.carbondata.hadoop.streaming.CarbonStreamRecordReader.scanBlockletAndFillVector(CarbonStreamRecordReader.java:423) at org.apache.carbondata.hadoop.streaming.CarbonStreamRecordReader.nextColumnarBatch(CarbonStreamRecordReader.java:317) at org.apache.carbondata.hadoop.streaming.CarbonStreamRecordReader.nextKeyValue(CarbonStreamRecordReader.java:298) at org.apache.carbondata.spark.rdd.CarbonScanRDD$$anon$1.hasNext(CarbonScanRDD.scala:298) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.scan_nextBatch$(Unknown Source) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377) at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:231) at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:225) at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:826) at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:826) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) at org.apache.spark.scheduler.Task.run(Task.scala:99) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) at java.lang.Thread.run(Thread.java:745) Caused by: org.apache.carbondata.core.scan.expression.exception.FilterUnsupportedException: [B cannot be cast to org.apache.spark.unsafe.types.UTF8String at org.apache.spark.sql.SparkUnknownExpression.evaluate(SparkUnknownExpression.scala:50) at org.apache.carbondata.core.scan.expression.conditional.GreaterThanEqualToExpression.evaluate(GreaterThanEqualToExpression.java:38) at org.apache.carbondata.core.scan.filter.executer.RowLevelFilterExecuterImpl.applyFilter(RowLevelFilterExecuterImpl.java:272) at org.apache.carbondata.core.scan.filter.executer.OrFilterExecuterImpl.applyFilter(OrFilterExecuterImpl.java:49) at org.apache.carbondata.hadoop.streaming.CarbonStreamRecordReader.scanBlockletAndFillVector(CarbonStreamRecordReader.java:418) ... 20 more Driver stacktrace: (state=,code=0) Expected : The select filter query should be success without error/exception. > (Carbon1.3.0 - Streaming) Error "Failed to filter row in vector reader" when filter query executed on streaming data > -------------------------------------------------------------------------------------------------------------------- > > Key: CARBONDATA-1783 > URL: https://issues.apache.org/jira/browse/CARBONDATA-1783 > Project: CarbonData > Issue Type: Bug > Components: data-query > Affects Versions: 1.3.0 > Environment: 3 node ant cluster > Reporter: Chetan Bhat > Labels: DFX > > Steps :- > Spark submit thrift server is started using the command - bin/spark-submit --master yarn-client --executor-memory 10G --executor-cores 5 --driver-memory 5G --num-executors 3 --class org.apache.carbondata.spark.thriftserver.CarbonThriftServer /srv/spark2.2Bigdata/install/spark/sparkJdbc/carbonlib/carbondata_2.11-1.3.0-SNAPSHOT-shade-hadoop2.7.2.jar "hdfs://hacluster/user/hive/warehouse/carbon.store" > Spark shell is launched using the command - bin/spark-shell --master yarn-client --executor-memory 10G --executor-cores 5 --driver-memory 5G --num-executors 3 --jars /srv/spark2.2Bigdata/install/spark/sparkJdbc/carbonlib/carbondata_2.11-1.3.0-SNAPSHOT-shade-hadoop2.7.2.jar > From Spark shell user creates table and loads data in the table as shown below. > import java.io.{File, PrintWriter} > import java.net.ServerSocket > import org.apache.spark.sql.{CarbonEnv, SparkSession} > import org.apache.spark.sql.hive.CarbonRelation > import org.apache.spark.sql.streaming.{ProcessingTime, StreamingQuery} > import org.apache.carbondata.core.constants.CarbonCommonConstants > import org.apache.carbondata.core.util.CarbonProperties > import org.apache.carbondata.core.util.path.{CarbonStorePath, CarbonTablePath} > CarbonProperties.getInstance().addProperty(CarbonCommonConstants.CARBON_TIMESTAMP_FORMAT, "yyyy/MM/dd") > import org.apache.spark.sql.CarbonSession._ > val carbonSession = SparkSession. > builder(). > appName("StreamExample"). > getOrCreateCarbonSession("hdfs://hacluster/user/hive/warehouse/carbon.store") > > carbonSession.sparkContext.setLogLevel("INFO") > def sql(sql: String) = carbonSession.sql(sql) > def writeSocket(serverSocket: ServerSocket): Thread = { > val thread = new Thread() { > override def run(): Unit = { > // wait for client to connection request and accept > val clientSocket = serverSocket.accept() > val socketWriter = new PrintWriter(clientSocket.getOutputStream()) > var index = 0 > for (_ <- 1 to 1000) { > // write 5 records per iteration > for (_ <- 0 to 100) { > index = index + 1 > socketWriter.println(index.toString + ",name_" + index > + ",city_" + index + "," + (index * 10000.00).toString + > ",school_" + index + ":school_" + index + index + "$" + index) > } > socketWriter.flush() > Thread.sleep(2000) > } > socketWriter.close() > System.out.println("Socket closed") > } > } > thread.start() > thread > } > > def startStreaming(spark: SparkSession, tablePath: CarbonTablePath, tableName: String, port: Int): Thread = { > val thread = new Thread() { > override def run(): Unit = { > var qry: StreamingQuery = null > try { > val readSocketDF = spark.readStream > .format("socket") > .option("host", "10.18.98.34") > .option("port", port) > .load() > qry = readSocketDF.writeStream > .format("carbondata") > .trigger(ProcessingTime("5 seconds")) > .option("checkpointLocation", tablePath.getStreamingCheckpointDir) > .option("tablePath", tablePath.getPath).option("tableName", tableName) > .start() > qry.awaitTermination() > } catch { > case ex: Throwable => > ex.printStackTrace() > println("Done reading and writing streaming data") > } finally { > qry.stop() > } > } > } > thread.start() > thread > } > val streamTableName = "all_datatypes_2048" > sql(s"create table all_datatypes_2048 (imei string,deviceInformationId int,MAC string,deviceColor string,device_backColor string,modelId string,marketName string,AMSize string,ROMSize string,CUPAudit string,CPIClocked string,series string,productionDate timestamp,bomCode string,internalModels string, deliveryTime string, channelsId string, channelsName string , deliveryAreaId string, deliveryCountry string, deliveryProvince string, deliveryCity string,deliveryDistrict string, deliveryStreet string, oxSingleNumber string, ActiveCheckTime string, ActiveAreaId string, ActiveCountry string, ActiveProvince string, Activecity string, ActiveDistrict string, ActiveStreet string, ActiveOperatorId string, Active_releaseId string, Active_EMUIVersion string, Active_operaSysVersion string, Active_BacVerNumber string, Active_BacFlashVer string, Active_webUIVersion string, Active_webUITypeCarrVer string,Active_webTypeDataVerNumber string, Active_operatorsVersion string, Active_phonePADPartitionedVersions string, Latest_YEAR int, Latest_MONTH int, Latest_DAY Decimal(30,10), Latest_HOUR string, Latest_areaId string, Latest_country string, Latest_province string, Latest_city string, Latest_district string, Latest_street string, Latest_releaseId string, Latest_EMUIVersion string, Latest_operaSysVersion string, Latest_BacVerNumber string, Latest_BacFlashVer string, Latest_webUIVersion string, Latest_webUITypeCarrVer string, Latest_webTypeDataVerNumber string, Latest_operatorsVersion string, Latest_phonePADPartitionedVersions string, Latest_operatorId string, gamePointDescription string,gamePointId double,contractNumber BigInt) STORED BY 'org.apache.carbondata.format' TBLPROPERTIES('streaming'='true','table_blocksize'='2048')") > sql(s"LOAD DATA INPATH 'hdfs://hacluster/chetan/100_olap_C20.csv' INTO table all_datatypes_2048 options ('DELIMITER'=',', 'BAD_RECORDS_ACTION'='FORCE','FILEHEADER'='imei,deviceInformationId,MAC,deviceColor,device_backColor,modelId,marketName,AMSize,ROMSize,CUPAudit,CPIClocked,series,productionDate,bomCode,internalModels,deliveryTime,channelsId,channelsName,deliveryAreaId,deliveryCountry,deliveryProvince,deliveryCity,deliveryDistrict,deliveryStreet,oxSingleNumber,contractNumber,ActiveCheckTime,ActiveAreaId,ActiveCountry,ActiveProvince,Activecity,ActiveDistrict,ActiveStreet,ActiveOperatorId,Active_releaseId,Active_EMUIVersion,Active_operaSysVersion,Active_BacVerNumber,Active_BacFlashVer,Active_webUIVersion,Active_webUITypeCarrVer,Active_webTypeDataVerNumber,Active_operatorsVersion,Active_phonePADPartitionedVersions,Latest_YEAR,Latest_MONTH,Latest_DAY,Latest_HOUR,Latest_areaId,Latest_country,Latest_province,Latest_city,Latest_district,Latest_street,Latest_releaseId,Latest_EMUIVersion,Latest_operaSysVersion,Latest_BacVerNumber,Latest_BacFlashVer,Latest_webUIVersion,Latest_webUITypeCarrVer,Latest_webTypeDataVerNumber,Latest_operatorsVersion,Latest_phonePADPartitionedVersions,Latest_operatorId,gamePointId,gamePointDescription')") > val carbonTable = CarbonEnv.getInstance(carbonSession).carbonMetastore. > lookupRelation(Some("default"), streamTableName)(carbonSession).asInstanceOf[CarbonRelation].carbonTable > val tablePath = CarbonStorePath.getCarbonTablePath(carbonTable.getAbsoluteTableIdentifier) > val port = 8007 > val serverSocket = new ServerSocket(port) > val socketThread = writeSocket(serverSocket) > val streamingThread = startStreaming(carbonSession, tablePath, streamTableName, port) > While the streaming load is in progress from Beeline user executes the below select filter query > select imei,gamePointId, channelsId,series from all_datatypes_2048 where channelsId >=10 OR channelsId <=1 and series='7Series'; > *Issue : The select filter query fails with exception as shown below.* > 0: jdbc:hive2://10.18.98.34:23040> select imei,gamePointId, channelsId,series from all_datatypes_2048 where channelsId >=10 OR channelsId <=1 and series='7Series'; > Error: org.apache.spark.SparkException: Job aborted due to stage failure: Task 6 in stage 773.0 failed 4 times, most recent failure: Lost task 6.3 in stage 773.0 (TID 33727, BLR1000014269, executor 14): java.io.IOException: Failed to filter row in vector reader > at org.apache.carbondata.hadoop.streaming.CarbonStreamRecordReader.scanBlockletAndFillVector(CarbonStreamRecordReader.java:423) > at org.apache.carbondata.hadoop.streaming.CarbonStreamRecordReader.nextColumnarBatch(CarbonStreamRecordReader.java:317) > at org.apache.carbondata.hadoop.streaming.CarbonStreamRecordReader.nextKeyValue(CarbonStreamRecordReader.java:298) > at org.apache.carbondata.spark.rdd.CarbonScanRDD$$anon$1.hasNext(CarbonScanRDD.scala:298) > at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.scan_nextBatch$(Unknown Source) > at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source) > at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) > at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377) > at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:231) > at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:225) > at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:826) > at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:826) > at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) > at org.apache.spark.scheduler.Task.run(Task.scala:99) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282) > at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) > at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) > at java.lang.Thread.run(Thread.java:745) > Caused by: org.apache.carbondata.core.scan.expression.exception.FilterUnsupportedException: [B cannot be cast to org.apache.spark.unsafe.types.UTF8String > at org.apache.spark.sql.SparkUnknownExpression.evaluate(SparkUnknownExpression.scala:50) > at org.apache.carbondata.core.scan.expression.conditional.GreaterThanEqualToExpression.evaluate(GreaterThanEqualToExpression.java:38) > at org.apache.carbondata.core.scan.filter.executer.RowLevelFilterExecuterImpl.applyFilter(RowLevelFilterExecuterImpl.java:272) > at org.apache.carbondata.core.scan.filter.executer.OrFilterExecuterImpl.applyFilter(OrFilterExecuterImpl.java:49) > at org.apache.carbondata.hadoop.streaming.CarbonStreamRecordReader.scanBlockletAndFillVector(CarbonStreamRecordReader.java:418) > ... 20 more > Driver stacktrace: (state=,code=0) > Expected : The select filter query should be success without 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